A side-by-side comparison of an AI Inventory or System Register and an AI Use Policy. Understand how a catalogue of AI systems differs from rules for acceptable organizational use.
Quick Verdict: Use an AI Inventory to record what AI systems and use cases exist; use an AI Use Policy to define how AI may and may not be used.
AI Inventory System Register describes organized catalogue of AI systems and use cases within an organization.
Context: Most relevant when an organization needs visibility over AI systems, use cases, risks, owners, and lifecycle status.
AI Use Policy describes internal governance document that defines how AI tools and systems may be used within an organization.
Context: Most relevant when setting organizational rules for acceptable, prohibited, approved, and escalated AI use.
| Aspect | [AI] Inventory [System Register] | [AI] Use Policy |
|---|---|---|
| Purpose | An AI inventory records which AI systems and use cases exist and how they are governed. | An AI use policy defines how AI tools and systems may be used within the organization. |
| Owner | Ownership usually sits with governance, risk, compliance, technology, or business-system owners. | Ownership usually sits with governance, legal, compliance, security, HR, or technology leadership. |
| Inputs | Inputs include system details, owners, purposes, data sources, deployment status, risks, and controls. | Inputs include organizational risk appetite, allowed use cases, prohibited use cases, data-handling rules, and escalation paths. |
| Outputs | Outputs include a searchable register, audit evidence, system ownership records, and lifecycle status. | Outputs include rules, responsibilities, approval requirements, monitoring expectations, and incident escalation guidance. |
| Audit trail | The audit trail shows what systems exist, who owns them, and what evidence supports their governance status. | The audit trail shows what rules were communicated and how use, approvals, exceptions, and incidents were managed. |
| Common mistake | A common mistake is building a static spreadsheet that is not linked to risk and control evidence. | A common mistake is issuing a policy without knowing which AI systems and uses already exist. |
In practice, the policy and inventory should reinforce each other. A policy without an inventory is hard to enforce, while an inventory without a policy lacks clear behavioral boundaries.
Treating an AI policy as a substitute for an AI inventory.
Keeping an inventory that records tools but not owners or purposes.
Writing AI use rules that do not address data handling and escalation.
Failing to update the inventory when teams adopt new AI tools.
Use an AI Inventory or System Register when the organization needs a structured record of AI systems, use cases, owners, purposes, data sources, risks, controls, and deployment status. It is the visibility layer for AI governance.
Use an AI Use Policy when the organization needs rules for acceptable and prohibited AI use, data handling, approvals, monitoring, and escalation. It is the behavioral and operational rulebook for users and teams.
AI inventories and use policies support governance under ISO/IEC 42001 and NIST AI RMF, and they help organizations prepare evidence for EU AI Act-related obligations where relevant. The inventory shows what exists; the policy shows how it should be used.
No. An AI inventory records systems and use cases, while an AI use policy defines how AI may be used within the organization.
They can be developed together. A basic policy sets immediate boundaries, while the inventory identifies actual systems and use cases that need governance.
It should record owners, purposes, data sources, deployment status, risks, controls, and other information needed for governance, audit, and accountability.
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